The present disclosure relates generally to control systems, predictive systems, and optimization systems that utilize empirical models with globally enforced general constraints.
Empirical models are typically used in the modeling of complex processes, including control systems, predictive systems, and optimization systems. During empirical modeling, historical data may be used as training data that aids in defining the empirical model. The trained empirical model, for example, embodied in a controller, may then present relatively accurate results within the range of the training data. However, when the trained model encounters inputs outside of the training range, the extrapolated results may not be as accurate. Further, other properties of the training data, such as quality of the data fit, may not be sufficient to render the empirical model useful.